Abstract
Robots for stroke rehabilitation at the lower limbs in sitting/lying position have been developed extensively. Some of them have been applied in clinics and shown the potential of the recovery of poststroke patients who suffer from hemiparesis. These robots were developed to provide training at different joints of lower limbs with various activities and modalities. This article reviews the training activities that were realized by rehabilitation robots in literature, in order to offer insights for developing a novel robot suitable for stroke rehabilitation. The control system of the lower limb rehabilitation robot in sitting position that was introduced in the previous work is discussed in detail to demonstrate the behavior of the robot while training a subject. The nonlinear impedance control law, based on active assistive control strategy, is able to define the response of the robot with more specifications while the passivity property and the robustness of the system is verified. A preliminary experiment is conducted on a healthy subject to show that the robot is able to perform active assistive exercises with various training activities and assist the subject to complete the training with desired level of assistance.
Highlights
Robots for rehabilitation have gained more attentions in many research due to some benefits over conventional therapy by physiotherapists
Robots for stroke rehabilitation have shown their effectiveness in many clinical trials worldwide
The magnitude of the error is usually high in low assistance training followed by medium and high assistance training
Summary
Robots for rehabilitation have gained more attentions in many research due to some benefits over conventional therapy by physiotherapists. Robots for locomotion training on a treadmill primarily aim to replace physical demand of the therapist labor because the task is ergonomically unfavorable and tiring [1]. Robots are able to obtain and record data such as position, velocity, interaction force, or biosignal with various kinds of sensors. This quantitative data can be used for further offline analysis, which leads to objective evaluation of the patient’s recovery [3, 4], or even used for adapting robot’s behavior corresponding the patient’s current condition. Rehabilitation robots are able to perform different types of exercises and varieties of movement [2, 7, 8]. Robots for stroke rehabilitation have shown their effectiveness in many clinical trials worldwide
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